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Record W2034304555 · doi:10.1198/106186001317243412

CriSP: A Tool for Bump Hunting

2001· article· en· W2034304555 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Computational and Graphical Statistics · 2001
Typearticle
Languageen
FieldMathematics
TopicAdvanced Statistical Methods and Models
Canadian institutionsnot available
Fundersnot available
KeywordsSmoothingBootstrapping (finance)Test statisticMathematicsResamplingStatisticFunction (biology)StatisticsStatistical hypothesis testingAlgorithmComputer scienceEconometrics

Abstract

fetched live from OpenAlex

We propose a test of multimodality of regression functions and their derivatives. The test statistic is a critical smoothing parameter (CriSP), giving the minimum amount of smoothing necessary to force the regression function to satisfy the null hypothesis. The p-values are computed via bootstrapping. Our idea is motivated by Silverman's test concerning the number of modes in the density function. Simulation studies indicate that the test works well, even when testing for bumps in the derivative. We apply CriSP to children's growth data, to study the number of spurts of growth. Key Words: Bootstrap; Critical smoothing parameter; Growth data; Multimodality testing; Smoothing Jarek Harezlak is a Biostatistician in the Division of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, 46202-2872 USA (e-mail jharezla@iupui.edu). Nancy Heckman is a Professor in the Department of Statistics, University of British Columbia, Vancouver BC V6T 1Z3 Canada (e-mail nancy@stat.ubc...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.089
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.076
GPT teacher head0.414
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it